Performance comparison of data compression algorithms for environmental monitoring wireless sensor networks

  • Authors:

  • Jonathan Gana Kolo;Li-Minn Ang;Kah Phooi Seng;S. R. S. Prabaharan

  • Affiliations:

  • Department of Electrical and Electronics Engineering, The University of Nottingham Malaysia Campus, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia;School of Engineering, Edith Cowan University, Joondalup, WA 6027, Australia;School of Computer Technology, Sunway University Malaysia, 5 Jalan Universiti, Bandar Sunway, 46150 Petaling Jaya, Selangor, Malaysia;Faculty of Engineering and Sciences, Manipal International University, Kelana Jaya, Selangor, Malaysia

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2013

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Abstract

Wireless sensor networks (WSNs) have serious resource limitations ranging from finite power supply, limited bandwidth for communication, limited processing speed, to limited memory and storage space. Data compression can help reduce memory and storage space requirements on sensor node. In WSNs, radio communication is the major consumer of energy. Therefore, applying data compression before transmission will significantly and directly help in reducing total power consumption of a sensor node thereby extending the network lifetime. In this article, we propose a simple lossless data compression algorithm designed specifically to be used by environmental monitoring sensor nodes for the compression of environmental data which are characterised by significant fluctuations in entropy. To verify the effectiveness of our proposed algorithm, we compare its compression performance with two existing WSNs compression algorithms using real-world environmental datasets. We show that our algorithm outperforms the other two algorithms when the entropy of the dataset is large.